The Epistemology of Observation: A Formal Certification Framework for Human and Automated Classifiers in DAG-OR
Abstract
Every classification system presupposes an observer. The Modulign Standard (DAG-OR) makes this presupposition explicit through the §OBS and §AUT segments of the dimensional address, which encode not merely who observed but at what level of certified competence. This paper provides the formal academic treatment of the %AUT Certification Framework, previously published as an appendix to the Modulign v3.1 specification [7]. We develop the epistemological foundations for a three-tier observer competence model—:T (Trained), :E (Evaluated), :A (Autonomous)—and argue that observer certification is not an administrative overlay on the classification grammar but a constitutive requirement of it. We specify the enforcement mechanisms for prohibited practices, the minimum evaluation requirements for each certification tier, the explainability requirements and their limits, the out-of-distribution detection mandates, and the constitutional constraints on automated observer testimony. We conclude with an honest assessment of the framework's limitations, including the certifier competence recursion and the conditions under which the framework would require revision.
Keywords: observer certification, epistemic competence, automated classification, explainability, AI governance, Confrontation Clause, dimensional address grammar
Cite it
Gonzalez, V. (2026). The Epistemology of Observation: A Formal Certification Framework for Human and Automated Classifiers in DAG-OR. Zenodo. https://doi.org/10.5281/zenodo.19726226